experiments set values, added csv files radius error and graphic stuff

tex/bare_conf.tex

@@ -13,10 +13,10 @@
 \history{Received: date; Accepted: date; Published: date}
 
 
-\usepackage{svg}
 
 \usepackage{color, colortbl}
 \usepackage{graphicx}
+\usepackage{subcaption}
 
 \interdisplaylinepenalty=2500
 
@@ -28,6 +28,7 @@
 \usepackage{siunitx}
 \usepackage{array}
 \usepackage{multirow}
+\usepackage{svg}
 
 %\updates{yes} % If there is an update available, un-comment this line
  

tex/chapters/experiments.tex

@@ -15,7 +15,7 @@ It was created using our 3D map editor software based on architectural drawings
 
 Sensor measurements are recorded using a simple mobile application that implements the standard Android sensor functionalities.
 As smartphones we used either a Samsung Note 2, Google Pixel One or Motorola Nexus 6.
-The computation of the state estimation as well as the \docWifi{} optimization are done offline using an Intel Core i7-4702HQ CPU with a frequency of \SI{2.2}{GHz} running \SI{8}{cores} and \SI{16}{GB} main memory. 
+The computation of the state estimation as well as the \docWIFI{} optimization are done offline using an Intel Core i7-4702HQ CPU with a frequency of \SI{2.2}{GHz} running \SI{8}{cores} and \SI{16}{GB} main memory. 
 However, similar to our previous, award-winning system, the setup is able to run completely on commercial smartphones as well as it uses C++ code \cite{torres2017smartphone}. 
 %Sensor measurements are recorded using a simple mobile application that implements the standard Android SensorManager. 
 
@@ -66,9 +66,9 @@ Other transmitters like smart TVs or smartphone hotspots are ignored as they mig
 \end{figure}
 %
 The 4 chosen walking paths can be seen in fig. \ref{fig:floorplan}. 
-Walk 0 is \SI{152}{\meter} long and took about \SI{2.30}{\minutes} to walk.
-Walk 2 has a length of \SI{223}{\meter} and Walk 3 a length of \SI{231}{\meter}, both required about \SI{6}{\minutes} to walk. 
-Finally, walk 3 is \SI{310}{\meter} long and needs \SI{10}{\minutes} to walk.
+Walk 0 is \SI{152}{\meter} long and took about \SI{2.30}{\minute} to walk.
+Walk 2 has a length of \SI{223}{\meter} and Walk 3 a length of \SI{231}{\meter}, both required about \SI{6}{\minute} to walk. 
+Finally, walk 3 is \SI{310}{\meter} long and needs \SI{10}{\minute} to walk.
 All walks were carried out be 4 different male testers using either a Samsung Note 2, Google Pixel One or Motorola Nexus 6 for recording the measurements. 
 All in all, we recorded \SI{28}{} distinct measurement series, \SI{7}{} for each walk.
 The picked walks intentionally contain erroneous situations, in which many of the above treated problems occur. 
@@ -146,17 +146,10 @@ Without a method to recover from impoverishment, the system lost track in \SI{10
 By using the simple method, the overall error can be reduced and the impoverishment resolved. Nevertheless, unpredictable jumps of the estimation are causing the system to be highly uncertain in some situations, even if those jumps do not last to long.
 Only the use of the $D_\text{KL}$ method is able to produce reasonable results.
 
-\begin{figure}[bt]
-	\centering
-  	\includegraphics[width=0.9\textwidth]{gfx/wifiOptGlobalFloor/combined_dummy.png}
-	\caption{A small section of walk 3. Optimizing the system with a global Wi-Fi optimization scheme (blue) causes a big jump and thus high errors. This happens due to highly attenuated Wi-Fi signals and inappropriate Wi-Fi parameters. We compare this to a system optimized for each floor individually (red), resolving the situation a producing reasonable results.}
-	\label{fig:wifiopt}
-\end{figure}
-%
 As described in chapter \ref{sec:wifi}, we use a Wi-Fi model optimized for each floor instead of a single global one.
 A good example why we do this, can be seen in fig. \ref{fig:wifiopt}, considering a small section of walk 3.
 Here, the system using the global Wi-Fi model makes a big jump into the right-hand corridor and requires \SI{5}{\second} to recover.
-This happens through a combination of environmental occurrences, like the many different materials and thus attenuation factors, as well as the limitation of the here used Wi-Fi model, only considering ceilings and ignoring walls. 
+This happens through a combination of environmental occurrences, like the many different materials and thus attenuation factors, as well as the limitation of the here used Wi-Fi model, only considering ceilings and ignoring walls.
 Following, \docAPshort{}'s on the same floor level, which are highly attenuated by \SI{2}{\meter} thick stone walls, are neglected and \docAPshort{}'s from the floor above, which are only separated by a thin wooden ceiling, have a greater influence within the state evaluation process.
 Of course, we optimize the attenuation per floor, but at the end this is just an average value summing up the \docAPshort{}'s surrounding materials. 
 Therefore, the calculated signal strength predictions do not fit the measurements received from the above in a optimal way.
@@ -164,6 +157,14 @@ In contrast, the model optimized for each floor only considers the respective \d
 A major disadvantage of the method is the reduced number of visible \docAPshort{}'s and thus measurements within an area. 
 This could lead to an underrepresentation of \docAPshort{}'s for triangulation.
 
+\begin{figure}[t!]
+	\centering
+  	\includegraphics[width=0.9\textwidth]{gfx/wifiOptGlobalFloor/combined_dummy.png}
+	\caption{A small section of walk 3. Optimizing the system with a global Wi-Fi optimization scheme (blue) causes a big jump and thus high errors. This happens due to highly attenuated Wi-Fi signals and inappropriate Wi-Fi parameters. We compare this to a system optimized for each floor individually (red), resolving the situation a producing reasonable results.}
+	\label{fig:wifiopt}
+\end{figure}
+
+
 %walk 1 
 Looking at the results of table \ref{table:overall} again, it can be seen that the $D_\text{KL}$ method is able to improve the results in three of the four walks. 
 Those walks have in common, that they suffer in some way from sample impoverishment or other problems causing the system to stuck. 
@@ -182,8 +183,8 @@ As a result, the radius $r_\text{sub}$ increases and thus the diversity of parti
 We are able to confirm the above by examining the different scenarios integrated into walk 1.
 For this, we compared the error development with the corresponding radius $r_\text{sub}$ over time. 
 In situations where the errors given by the $D_\text{KL}$ method and the simple method differ the most, $r_\text{sub}$ also increases the most. 
-Here, the radius grows to a maximum of $r_\text{sub} = $ \SI{666}{\meter}.
-In contrast, a real sample impoverishment scenario, as seen in walk 0 (cf. fig. \ref{fig:errorOverTimeWalk0}), provides a maximum radius of \SI{777}{\meter}.
+Here, the radius grows to a maximum of $r_\text{sub} = $ \SI{8.4}{\meter}, using the same measurement series as in fig. \ref{fig:walk1:kdeovertime}.
+In contrast, a real sample impoverishment scenario, as seen in walk 0 (cf. fig. \ref{fig:errorOverTimeWalk0}), has a maximum radius of \SI{19.6}{\meter}.
 Nevertheless, such an slightly increased diversity is enough to influence the estimation error of the $D_\text{KL}$ in a negative way (cf. walk 1 in table \ref{table:overall}). 
 Ironically, this is again some type of sample impoverishment, caused by the aforementioned environmental restrictions not allowing particles inside walls or other out of reach areas. 
 
@@ -191,21 +192,32 @@ Ironically, this is again some type of sample impoverishment, caused by the afor
 \subsection{Estimation}
 \label{sec:eval:est}
 
+\todo{boxkde 0.2 point2(1,1);}
+
 As mentioned before, the single estimation methods (cf. chapter \ref{sec:estimation}) only vary by a few centimetres in the overall localization error. 
 That means, they differ mainly in the representation of the estimated locations. 
 More easily spoken, in which way the estimated path is drawn and thus presented to the user.
 Regarding the underlying particle set, different shapes of probability distributions need to be considered, especially those with multimodalities. 
 %
-\begin{figure}
+\begin{figure}[t]
 	\centering
-	\input{gfx/walk.tex}
-	\caption{Occurring bimodal distribution caused by uncertain measurements in the first \SI{13.4}{\second} of walk 1. After \SI{20.8}{\second}, the distribution gets unimodal. The weigted-average estimation (blue) provides a high error compared to the ground truth (solid black), while the KDE approach (orange) does not. }
-	\label{fig:realWorldMulti}
+	\begin{subfigure}{0.48\textwidth}
+		\resizebox{1\textwidth}{!}{\input{gfx/walk.tex}}
+        \caption{}
+        \label{fig:walk1:kde}
+    \end{subfigure}
+	\begin{subfigure}{0.50\textwidth}
+		\resizebox{1\textwidth}{!}{\input{gfx/errorOverTimeWalk1/errorOverTime.tex}}
+        \caption{}
+        \label{fig:walk1:kdeovertime}
+    \end{subfigure}
+	\caption{(a) Occurring bimodal distribution caused by uncertain measurements in the first \SI{13.4}{\second} of walk 1. After \SI{20.8}{\second}, the distribution gets unimodal. The weigted-average estimation (blue) provides a high error compared to the ground truth (solid black), while the KDE approach (orange) does not. (b) Error development over time for the complete walk. From \SI{230}{\second} to \SI{290}{\second} to pedestrian was not moving. }
+	\label{fig:walk1}
 \end{figure}
 %
 The main advantage of a KDE-based estimation is that it provides the "correct" mode of a density, even under a multimodal setting (cf. section \ref{sec:estimation}). 
 That is why we again have a look at walk 1.
-A situation in which the system highly benefits from this is illustrated in fig. \ref{fig:realWorldMulti}.
+A situation in which the system highly benefits from this is illustrated in fig. \ref{fig:walk1:kde}.
 Here, a set of particles splits apart, due to uncertain measurements and multiple possible walking directions.
 Indicated by the black dotted line, the resulting bimodal posterior reaches its maximum distance between the modes at \SI{13.4}{\second}.
 Thus, a weighted average estimation (blue line) results in a position of the pedestrian somewhere outside the building (light green area). 
@@ -214,8 +226,8 @@ The KDE-based estimation (orange line) is able to provide reasonable results by
 After \SI{20.8}{\second} the setting returns to be unimodal again. 
 Due to a right turn the lower red particles are walking against a wall and thus punished with a low weight.
 
-Although, situations as displayed in fig. \ref{fig:realWorldMulti} frequently occur, the KDE-estimation is not able to improve the overall estimation results.
-This can be seen in the corresponding error development over time plot given by fig. \ref{fig:realWorldTime}. 
+Although, situations as displayed in fig. \ref{fig:walk1:kde} frequently occur, the KDE-estimation is not able to improve the overall estimation results.
+This can be seen in the corresponding error development over time plot given by fig. \ref{fig:walk1:kdeovertime}. 
 Here, the KDE-estimation performs slightly better then the weighted-average, however after deploying \SI{100}{} Monte Carlo runs, the difference becomes insignificant.
 It is obvious, that the above mentioned "correct" mode, not always provides the lowest error. 
 In some situations the weighted-average estimation is often closer to the ground truth. 
@@ -223,30 +235,22 @@ Within our experiments this happened especially when entering or leaving thick-w
 While the system’s dynamics are moving the particles outside, the faulty Wi-Fi readings are holding back a majority by assigning corresponding weights.
 Only with new measurements coming from the hallway or other parts of the building, the distribution and thus the KDE-estimation are able to recover. 
 
-\begin{figure}
-	\centering
-	\input{gfx/errorOverTimeWalk1/errorOverTime.tex}
-	\caption{Error development over time of a single Monte Carlo run of the walk calculated between estimation and ground truth. Between \SI{230}{\second} and \SI{290}{\second} to pedestrian was not moving.}
-	\label{fig:realWorldTime}
-\end{figure}
-
 This leads to the conclusion, that a weighted average approach provides a more smooth representation of the estimated locations and thus a higher robustness.
 
-\todo{bild vom gesamten walk 2 und den unterschied zwischen weighted average estimation und kde estimation zeigen. wie sich das auf dne estimated path auswirkt. also der eine pfad springt viel und der andere ist halt smoother}
+\todo{bild vom gesamten walk 2 und den unterschied zwischen weighted average estimation und kde estimation zeigen. wie sich das auf dne estimated path auswirkt. also der eine pfad springt viel und der andere ist halt smoother
+
+vielleicht noch fig. 8 raus dafür. }
 
 In contrast, a KDE-based approach for estimation is able to resolve multimodalities. 
 It does not always provide the lowest error, since it depends more on an accurate sensor model then a weighted average approach, but is very suitable as a good indicator about the real performance of a sensor fusion system. 
 At the end, in the here shown examples we only searched for a global maxima, even though this approach opens a wide range of other possibilities for finding a best estimate.
 
-\todo{boxkde 0.2 point2(1,1);}
-
-\todo{
-BILD: Von einem Pfad der steckenbleibt und den beiden anderen verfahren mit fehler über die zeit. 
-
-BILD: WIFI-Fehler unten bei den Kellern. 
-
-BILD: Estimation Fehler 
-}
+\begin{figure}[t]
+	\centering
+	\input{gfx/errorOverTimeWalk1/errorOverTime.tex}
+	\caption{Error development over time of a single Monte Carlo run of the walk calculated between estimation and ground truth. Between \SI{230}{\second} and \SI{290}{\second} to pedestrian was not moving.}
+	\label{}
+\end{figure}
 
 
 

tex/gfx/estimationPath2/kdeError.csv

@@ -0,0 +1,392 @@
+3186 2.15083
+3770 1.21742
+4546 1.47054
+5256 1.71075
+5808 2.591
+6455 3.88454
+6885 2.24605
+7426 2.30156
+7847 2.0852
+8465 3.84898
+9164 2.98921
+9981 3.5366
+10630 4.10365
+11267 4.99756
+11799 5.84838
+12280 6.19936
+12763 6.50442
+13321 6.96317
+13762 7.24985
+14227 7.60722
+14801 7.99275
+15485 8.13255
+16207 7.08064
+16779 5.92485
+17256 5.81206
+18038 4.58742
+18718 3.41794
+19543 2.03799
+20105 2.0748
+21632 3.02901
+22459 3.38219
+22860 1.90745
+23351 1.29709
+24001 1.36845
+24595 1.28835
+25196 1.3635
+25795 1.61066
+26369 1.27756
+26939 1.29791
+27594 1.09581
+28131 0.904428
+28829 1.16587
+29353 1.16578
+30032 1.18986
+30607 1.04974
+31467 0.694273
+33429 0.655747
+39246 0.683119
+41001 1.44465
+42181 1.6056
+45666 0.900055
+47220 1.82059
+47846 2.8277
+48707 3.63647
+49114 4.62094
+49813 4.79346
+50530 4.94515
+51121 5.18249
+51762 4.39385
+52292 4.91388
+52916 5.18586
+53559 4.61144
+54373 3.90235
+55035 3.55974
+55673 3.74122
+56396 4.22141
+57197 6.88859
+57936 6.75504
+58433 6.78235
+59176 7.13282
+59952 6.9967
+60851 4.05356
+61469 4.50973
+64492 3.61535
+66534 2.92166
+67210 2.19284
+67771 3.12549
+68460 3.21983
+69172 4.33233
+69888 2.94631
+70508 2.2234
+71198 2.35319
+72003 1.75293
+72601 1.95005
+73134 1.65783
+73895 1.75944
+74602 1.57017
+75257 2.44627
+76056 1.62047
+76753 1.99531
+77334 1.72614
+78034 1.74691
+78654 2.93972
+79299 3.20482
+79975 3.14424
+81076 3.75112
+81654 3.7813
+82490 3.80428
+84656 2.69451
+86347 2.59716
+88250 2.3463
+89052 1.85133
+89791 1.38364
+90453 0.783208
+91089 1.10465
+91787 2.03298
+92901 1.32241
+98165 3.07935
+101418 3.84001
+102047 3.446
+102828 3.85122
+103496 4.38836
+104244 5.06213
+104915 6.13096
+105576 4.53354
+106211 4.08721
+106835 3.67252
+107342 3.99146
+107995 4.43589
+108715 3.42598
+109255 3.11057
+109930 3.65448
+110512 3.89943
+111291 2.97453
+111796 2.67317
+112434 2.18755
+113217 5.31864
+124640 1.67091
+126777 1.50305
+133484 3.55585
+134815 4.99877
+135224 5.40836
+135724 6.24915
+136395 6.41157
+136982 6.50426
+137633 5.90694
+138257 6.10334
+138901 3.70469
+139569 1.31378
+140075 2.08445
+140700 1.87698
+141232 1.27499
+141900 1.8953
+142419 1.96679
+143076 2.54105
+143786 3.52956
+144434 3.96877
+145078 5.14683
+145806 6.34833
+146356 7.00721
+147000 6.91937
+147625 7.89856
+148213 7.60568
+148848 5.83734
+149584 5.49206
+150092 4.45343
+150796 3.8866
+151284 3.453
+151929 3.24918
+152621 3.32139
+153241 4.18304
+153910 4.46946
+154589 4.87306
+155259 5.3219
+156019 4.6242
+156669 2.94991
+157624 4.4734
+158139 4.59122
+158640 4.48756
+159281 5.16156
+159843 2.32503
+160485 2.52344
+161077 2.7018
+161679 3.50159
+162205 3.87825
+162840 3.93691
+163380 4.33706
+163927 4.75844
+164644 5.24963
+165214 5.84083
+165838 6.57225
+166416 7.37745
+166973 7.90611
+167561 8.20414
+168195 8.87551
+168935 7.03014
+169455 5.25347
+170089 4.85727
+170811 4.61956
+171416 4.42266
+171970 4.29564
+172509 5.12592
+173151 5.4268
+173695 8.77519
+174330 9.42076
+174996 9.34712
+175752 8.4968
+176406 4.71268
+177147 2.06131
+177745 1.72003
+178430 1.92941
+179046 2.19938
+179783 2.31215
+180404 2.5775
+180932 2.46156
+181626 2.29071
+182202 2.57881
+182845 2.5353
+183385 1.91376
+184021 1.53809
+184525 1.28858
+185172 0.976123
+185691 0.655172
+186203 0.682656
+186864 0.765914
+187466 1.29749
+188221 5.4341
+188943 6.75069
+189513 3.38999
+190218 1.58964
+190745 1.13933
+191462 1.20467
+191968 1.46862
+192557 3.31729
+193163 4.02164
+193826 4.80761
+194397 5.12324
+195125 6.49168
+195755 6.64895
+196544 6.02778
+197138 5.45922
+197716 4.68303
+198335 4.61405
+198937 3.88667
+199576 1.85048
+200222 1.69538
+200936 2.7862
+201557 2.58079
+202293 3.68706
+203155 2.87893
+203831 3.04421
+204488 3.29131
+204939 3.50539
+205376 3.75475
+205996 4.05506
+206396 3.80762
+206799 2.78252
+207526 2.97462
+207928 3.31978
+208493 3.07651
+209176 3.14444
+209888 3.44741
+210587 3.92581
+211269 4.6387
+212134 5.13274
+212911 5.70268
+213729 3.68651
+220694 5.2636
+221320 5.53558
+223839 6.25017
+224401 6.64295
+224961 6.59861
+225538 6.22573
+226237 5.04528
+226995 4.27538
+227578 4.18006
+228206 4.05759
+228841 4.14293
+229518 3.52529
+230222 3.3962
+230860 2.82687
+231503 2.76408
+232037 2.21801
+232639 2.12391
+233181 2.04432
+233830 2.4316
+234353 2.33801
+234998 2.3908
+235630 2.42805
+236170 2.59517
+236748 2.56752
+237336 2.71277
+237954 2.91856
+238511 2.75997
+239134 3.02829
+239735 3.48119
+240393 4.01313
+241067 3.36777
+241706 3.19287
+242326 3.16284
+242952 3.13883
+243604 2.39994
+244305 2.35025
+244863 2.38627
+245553 2.3157
+246465 3.24689
+246867 3.08701
+247404 1.10413
+248028 1.15508
+248585 1.20258
+249211 1.57569
+249765 1.9943
+250500 2.56418
+251064 2.20548
+251758 1.7537
+252287 1.67769
+252925 1.75126
+253623 1.1779
+254325 1.67521
+254858 2.13579
+260516 0.434785
+261083 0.163806
+261770 1.23621
+262442 2.48859
+263321 2.24183
+263836 2.09646
+267998 3.01868
+268617 2.56169
+269249 2.39397
+269968 2.54349
+270708 2.86344
+271368 4.07416
+271985 4.73173
+272624 5.22137
+273253 5.42053
+273850 5.41696
+274370 5.1637
+274946 4.52026
+275565 4.31561
+276106 3.91012
+276745 1.20575
+277330 1.56181
+277933 1.57495
+278644 0.905891
+279222 1.39965
+279883 2.02427
+280522 2.27501
+281202 2.29593
+281905 2.29819
+282523 1.81352
+283198 1.32918
+283819 1.76393
+284588 1.90705
+285137 1.75636
+285779 1.17207
+286419 1.8701
+287099 1.83662
+287695 1.68563
+288356 1.81594
+288895 1.8198
+289598 1.54915
+290216 1.5767
+290944 0.715638
+291513 0.415965
+292225 0.727297
+292816 1.60093
+293574 1.24655
+294118 1.16669
+294754 1.3181
+295452 1.27779
+296096 1.98047
+296793 3.00384
+297474 4.32481
+298114 4.39477
+298900 5.49072
+299610 5.46499
+300295 2.87995
+300910 1.33352
+301567 1.68264
+302230 2.26513
+302969 3.10449
+303527 3.54884
+303948 3.81918
+304590 4.05152
+304991 4.18864
+305585 4.16411
+306234 3.84436
+306649 3.636
+307231 3.20019
+307884 2.4113
+308511 3.38305
+309264 3.17932
+309863 2.03515
+310465 1.8516
+311227 1.7846
+312017 2.02965
+========================================================== 
+Average of all statistical data: 
+Median: 3.11057
+Average: 3.39862
+Standard Deviation: 1.85136
+75 Quantil: 4.50973

tex/gfx/estimationPath2/kdePath.csv

@@ -0,0 +1,386 @@
+62.0683 20.5943 2.1
+60.0108 19.4871 2.2
+60.0108 19.7639 2.3
+60.5252 19.7639 2.1
+61.2968 19.7639 2
+62.0683 19.7639 2.2
+58.7249 20.3175 2.5
+58.4678 20.3175 2.5
+57.6962 19.7639 2.5
+60.268 20.0407 2.6
+56.9247 19.4871 2.8
+57.6962 19.4871 3
+57.439 18.3798 3.2
+56.9247 18.3798 3.5
+57.439 18.103 3.7
+57.1818 18.103 3.9
+57.439 17.8262 4
+57.439 17.5494 4.1
+57.439 17.2726 4.2
+57.439 17.2726 4.3
+56.6675 17.5494 4.4
+57.439 17.5494 4.5
+57.1818 17.8262 4.7
+58.9821 15.6118 4.9
+59.2393 15.6118 5.2
+59.4965 15.6118 5.4
+59.4965 15.6118 5.5
+59.4965 15.6118 5.5
+59.4965 15.6118 5.6
+59.4965 15.6118 5.7
+59.4965 15.8886 5.8
+61.0396 16.719 5.9
+61.5539 17.8262 5.9
+61.8111 18.103 5.9
+62.3255 18.3798 5.9
+62.8399 18.6567 5.9
+63.097 18.9335 5.9
+63.3542 19.7639 5.9
+63.6114 20.3175 5.9
+63.3542 21.1479 5.9
+63.3542 21.9783 5.9
+63.3542 22.5319 5.9
+62.8399 22.8087 5.9
+63.097 23.916 5.9
+62.8399 24.7464 5.9
+62.3255 25.5768 5.9
+61.8111 26.684 5.9
+62.0683 27.5144 5.9
+61.5539 28.0681 5.9
+61.5539 28.3449 5.9
+62.8399 27.7913 5.9
+62.3255 27.5144 5.9
+62.3255 26.4072 5.9
+62.0683 25.8536 5.9
+63.6114 24.4696 5.9
+63.3542 24.4696 5.9
+63.3542 24.4696 5.9
+62.8399 24.4696 5.9
+63.3542 25.3 5.9
+62.8399 25.0232 5.9
+63.3542 24.7464 5.9
+62.8399 25.5768 5.9
+63.3542 26.1304 5.9
+64.1258 26.1304 5.9
+63.8686 26.4072 5.9
+64.1258 25.8536 5.9
+62.0683 24.7464 5.9
+61.8111 25.0232 5.9
+61.5539 25.3 5.9
+61.0396 25.3 5.9
+61.0396 25.8536 5.9
+64.1258 26.4072 5.9
+64.383 27.7913 5.9
+69.2694 28.6217 5.9
+69.0123 27.7913 5.9
+68.7551 26.9608 5.9
+70.041 27.7913 5.9
+70.2982 27.7913 5.9
+70.2982 28.8985 5.9
+69.7838 27.5144 5.9
+68.2407 26.1304 5.9
+68.2407 26.1304 5.9
+67.7263 24.1928 5.9
+68.2407 24.1928 5.9
+67.9835 23.6392 5.9
+68.2407 23.3624 5.9
+68.2407 22.8087 5.9
+68.4979 23.3624 5.9
+67.9835 21.9783 5.9
+67.9835 21.9783 5.9
+67.4692 18.9335 5.9
+67.7263 18.3798 5.9
+66.9548 17.2726 5.9
+67.212 16.4422 5.9
+67.7263 15.8886 5.9
+67.212 15.0582 5.9
+67.9835 14.5046 5.9
+67.9835 14.2278 5.9
+68.7551 14.7814 5.9
+68.4979 14.5046 5.9
+67.7263 14.2278 5.9
+66.9548 14.5046 5.9
+66.9548 14.7814 5.9
+67.212 15.335 5.9
+67.7263 15.6118 5.9
+68.4979 15.8886 5.9
+64.8973 15.6118 5.9
+64.8973 16.719 5.9
+64.8973 16.719 5.9
+65.4117 16.4422 5.9
+65.4117 16.719 5.9
+65.4117 16.9958 5.9
+64.8973 16.719 5.9
+64.8973 17.2726 5.9
+67.9835 15.6118 5.9
+67.9835 14.5046 5.9
+68.2407 13.3973 5.9
+66.4404 13.1205 5.9
+66.1832 12.8437 5.9
+68.2407 11.1829 5.9
+67.9835 10.3525 5.9
+68.4979 10.0757 5.9
+69.0123 9.52205 5.9
+67.7263 8.13802 5.9
+67.7263 7.3076 5.9
+67.212 6.20038 5.9
+64.6401 7.86122 5.9
+65.9261 7.58441 5.9
+67.212 6.20038 5.9
+67.9835 6.47719 5.9
+66.4404 5.64677 5.9
+66.4404 5.36996 5.9
+65.9261 4.81635 5.9
+66.1832 4.81635 5.9
+68.7551 4.81635 5.9
+68.7551 5.64677 5.9
+69.7838 5.92357 5.9
+69.0123 8.41483 5.9
+68.2407 10.9061 5.9
+68.4979 10.3525 5.9
+68.7551 10.9061 5.9
+67.7263 11.4597 5.9
+67.212 11.1829 5.9
+67.7263 11.1829 5.9
+68.4979 10.9061 5.9
+68.4979 10.6293 5.9
+67.7263 11.1829 5.9
+65.9261 11.1829 5.9
+65.4117 11.1829 5.9
+67.9835 11.4597 5.9
+67.4692 12.5669 5.9
+67.7263 12.2901 5.9
+66.9548 12.8437 5.9
+67.4692 15.0582 5.9
+67.7263 15.8886 5.9
+67.212 17.2726 5.9
+67.212 18.3798 5.9
+66.6976 19.2103 5.9
+66.1832 19.7639 5.9
+65.6689 20.0407 5.9
+65.1545 19.4871 5.9
+65.1545 19.4871 5.9
+65.4117 19.4871 5.9
+68.2407 21.1479 5.9
+68.2407 23.3624 5.9
+65.4117 23.6392 5.9
+68.2407 26.684 5.9
+68.2407 27.2376 5.9
+67.9835 27.5144 5.9
+68.4979 28.0681 5.9
+62.8399 27.2376 5.9
+62.3255 27.7913 5.9
+64.1258 28.3449 5.9
+63.8686 28.0681 5.9
+64.1258 28.3449 5.9
+63.8686 28.8985 5.9
+64.1258 29.1753 5.9
+64.383 29.4521 5.9
+64.383 29.7289 5.9
+64.383 29.7289 5.9
+63.8686 29.4521 5.9
+63.6114 29.1753 5.9
+63.3542 29.1753 5.9
+63.097 29.4521 5.9
+63.097 29.4521 5.9
+62.3255 31.3897 5.9
+62.5827 33.6042 5.9
+62.0683 34.1578 5.9
+61.2968 34.4346 5.9
+61.2968 35.265 5.9
+61.2968 36.3722 5.9
+61.8111 36.9259 5.9
+61.5539 37.4795 5.9
+64.1258 36.0954 5.9
+64.1258 36.0954 5.9
+63.3542 36.0954 5.9
+61.8111 36.6491 5.9
+57.6962 38.5867 5.9
+54.61 38.8635 5.9
+53.0669 38.3099 5.9
+52.2954 38.5867 5.9
+51.781 38.8635 5.9
+51.781 39.6939 5.9
+51.5238 40.2475 5.9
+51.5238 41.0779 5.9
+51.2666 42.1852 5.9
+50.7523 42.7388 5.9
+50.4951 43.5692 5.9
+50.4951 44.1228 5.9
+49.2092 44.6764 5.9
+48.6948 44.9532 5.9
+48.1804 45.23 5.9
+47.9232 45.5068 5.9
+47.4089 45.5068 5.9
+46.8945 45.5068 5.9
+47.1517 45.7837 5.9
+50.4951 45.7837 5.9
+51.0094 46.0605 5.9
+46.8945 45.5068 5.9
+44.5799 46.0605 5.9
+44.0655 45.7837 5.9
+43.5511 45.5068 5.9
+43.0368 45.23 5.9
+41.7508 46.0605 5.9
+41.2365 45.7837 5.9
+40.7221 45.5068 5.9
+40.4649 44.9532 5.9
+39.4362 44.9532 5.9
+39.179 44.1228 5.9
+38.9218 43.5692 5.9
+38.9218 43.2924 5.9
+38.9218 42.7388 5.9
+38.4075 42.7388 5.9
+38.4075 42.1852 5.9
+38.6646 40.2475 5.9
+39.179 39.4171 5.9
+39.6934 39.1403 5.9
+39.4362 39.1403 5.9
+40.4649 39.4171 5.9
+39.179 39.6939 5.9
+38.6646 39.6939 5.9
+38.4075 40.5243 5.9
+38.1503 41.0779 5.9
+38.1503 41.9084 5.9
+37.3787 41.0779 5.8
+37.1216 41.6316 5.6
+37.1216 42.1852 5.2
+37.1216 42.1852 5
+37.1216 42.1852 4.9
+37.1216 42.462 4.7
+37.1216 42.7388 4.7
+37.1216 42.7388 4.6
+37.1216 42.7388 4.5
+37.1216 42.7388 4.7
+37.3787 43.0156 4.8
+37.1216 42.1852 4.8
+36.35 44.9532 5
+38.1503 46.6141 5.3
+38.1503 46.6141 5.4
+38.1503 46.8909 5.5
+38.1503 47.1677 5.5
+38.1503 47.4445 5.4
+38.1503 47.7213 5
+37.1216 46.8909 4.8
+36.35 46.6141 4.5
+36.35 46.6141 4.3
+36.6072 46.3373 4
+36.35 46.3373 4
+36.0928 45.5068 4
+35.8356 44.9532 4
+35.3213 43.5692 4.2
+34.8069 42.7388 4.1
+33.521 43.0156 4
+32.7494 42.7388 3.9
+31.9779 42.7388 3.9
+31.4635 43.0156 3.9
+30.692 43.0156 3.9
+29.9204 43.0156 3.9
+29.1489 43.0156 3.9
+28.6345 43.0156 3.9
+27.863 43.0156 3.9
+27.3486 42.7388 3.9
+26.577 43.2924 3.9
+25.8055 43.0156 3.9
+25.2911 43.0156 3.9
+24.7768 43.5692 3.9
+24.2624 44.3996 3.9
+23.4908 44.6764 3.9
+23.2337 44.9532 3.9
+22.9765 45.5068 3.9
+22.7193 46.0605 3.9
+21.6906 45.7837 3.9
+20.919 46.0605 3.9
+20.4046 46.0605 3.9
+19.6331 46.0605 3.9
+19.6331 46.3373 3.9
+18.6044 44.9532 3.9
+16.2897 46.0605 3.9
+15.5182 46.0605 3.9
+14.7466 46.0605 3.9
+14.4894 46.0605 3.9
+13.9751 45.7837 3.9
+13.4607 45.5068 3.9
+12.9463 45.23 3.9
+12.6892 44.9532 3.9
+12.432 44.3996 3.9
+12.1748 43.5692 3.9
+11.6604 43.2924 3.9
+12.1748 42.7388 3.9
+12.432 42.1852 3.9
+11.4032 42.7388 3.9
+11.6604 43.0156 3.9
+10.8889 43.5692 3.9
+10.1173 44.3996 3.9
+10.6317 44.1228 3.9
+11.1461 44.1228 3.9
+11.4032 43.5692 3.9
+12.1748 43.2924 3.9
+13.2035 43.2924 3.9
+13.7179 43.2924 3.9
+14.2323 43.2924 3.9
+14.4894 43.846 3.9
+14.7466 43.846 3.9
+14.2323 43.846 3.9
+13.4607 43.5692 3.9
+11.9176 43.0156 3.9
+13.7179 42.1852 3.9
+13.2035 41.0779 3.9
+13.2035 40.2475 3.9
+13.4607 39.1403 3.9
+11.6604 33.881 3.9
+11.6604 33.0506 3.9
+11.4032 32.497 3.9
+10.8889 32.497 3.9
+10.1173 31.9433 3.9
+9.86014 31.6665 3.9
+9.08859 31.6665 3.9
+8.31704 31.9433 3.9
+7.54549 31.9433 3.9
+7.28831 31.6665 3.9
+7.54549 32.2202 3.9
+7.03113 33.0506 3.9
+6.51676 32.7738 3.9
+6.77394 32.497 3.9
+7.03113 31.6665 3.9
+9.60296 31.3897 3.9
+10.1173 31.3897 3.9
+10.6317 31.1129 3.9
+10.8889 31.3897 3.9
+10.8889 31.3897 3.9
+11.9176 30.8361 3.9
+12.432 30.8361 3.9
+12.6892 30.8361 3.9
+12.9463 30.8361 3.9
+12.9463 31.1129 3.9
+12.9463 30.8361 3.9
+12.1748 31.3897 3.9
+11.4032 31.6665 3.9
+10.8889 31.6665 3.9
+10.6317 31.9433 3.9
+11.1461 31.9433 3.9
+11.4032 31.6665 3.9
+11.9176 31.1129 3.9
+10.8889 31.6665 3.9
+11.4032 31.3897 3.9
+11.9176 31.9433 3.9
+10.8889 34.7114 3.9
+10.3745 36.9259 3.9
+9.86014 37.2027 3.9
+9.86014 37.2027 3.9
+10.1173 37.2027 3.9
+9.86014 37.2027 3.9
+9.34577 36.9259 3.9
+7.03113 36.6491 3.9
+7.80268 37.2027 3.9
+8.31704 37.4795 3.7
+8.31704 37.7563 3.5
+8.31704 38.0331 3.3
+7.80268 38.3099 3
+3.17338 36.6491 2.8
+7.28831 38.3099 2.7
+6.77394 38.3099 2.6
+3.43056 36.3722 2.5
+4.20211 36.6491 2.5
+3.94493 36.6491 2.5
+3.68775 36.3722 2.5

tex/gfx/estimationPath2/mvgError.csv

@@ -0,0 +1,392 @@
+3186 1.57708
+3770 1.43219
+4546 1.74629
+5256 1.8586
+5808 2.58236
+6455 2.43018
+6885 2.76868
+7426 2.98421
+7847 3.04315
+8465 3.23412
+9164 3.61928
+9981 4.0409
+10630 4.45665
+11267 5.28238
+11799 6.03766
+12280 6.37766
+12763 6.69258
+13321 7.06314
+13762 7.33069
+14227 7.60702
+14801 7.84003
+15485 7.91441
+16207 6.65426
+16779 5.77051
+17256 5.54489
+18038 4.35748
+18718 3.3685
+19543 2.22111
+20105 1.94961
+21632 2.49821
+22459 2.19055
+22860 1.64452
+23351 1.36595
+24001 1.25007
+24595 1.14355
+25196 1.36199
+25795 1.53128
+26369 1.64583
+26939 1.60025
+27594 1.42553
+28131 1.37605
+28829 1.4209
+29353 1.27815
+30032 0.654148
+30607 0.948147
+31467 1.31069
+33429 1.15582
+39246 0.397705
+41001 0.1061
+42181 0.103886
+45666 0.927077
+47220 1.42893
+47846 1.88701
+48707 2.37431
+49114 2.82411
+49813 3.19976
+50530 3.43221
+51121 3.54761
+51762 3.24077
+52292 3.23391
+52916 3.3068
+53559 2.87601
+54373 2.36347
+55035 2.24981
+55673 2.24999
+56396 2.44059
+57197 2.68092
+57936 3.05391
+58433 3.14855
+59176 3.32709
+59952 3.48146
+60851 3.76671
+61469 3.85207
+64492 4.06572
+66534 3.52143
+67210 3.15275
+67771 3.05958
+68460 3.13135
+69172 3.48929
+69888 2.89721
+70508 2.85102
+71198 2.72256
+72003 1.97729
+72601 2.26197
+73134 1.81293
+73895 1.53865
+74602 1.62257
+75257 1.70318
+76056 1.58064
+76753 1.73009
+77334 1.67297
+78034 2.11789
+78654 2.77066
+79299 3.19516
+79975 3.56734
+81076 3.78516
+81654 3.59707
+82490 3.58052
+84656 2.74084
+86347 2.20698
+88250 1.76624
+89052 1.42871
+89791 1.05858
+90453 0.719188
+91089 0.616982
+91787 0.9116
+92901 1.33538
+98165 2.14117
+101418 2.89502
+102047 3.32638
+102828 3.57072
+103496 3.9511
+104244 4.45711
+104915 5.24983
+105576 5.06608
+106211 4.51668
+106835 4.45379
+107342 3.67706
+107995 3.44907
+108715 3.44179
+109255 3.6249
+109930 4.06786
+110512 3.77808
+111291 3.81207
+111796 3.30325
+112434 3.22271
+113217 3.63445
+124640 0.719616
+126777 0.872469
+133484 3.59208
+134815 4.76996
+135224 5.16756
+135724 5.90591
+136395 6.59953
+136982 6.06443
+137633 5.51436
+138257 4.1518
+138901 3.05982
+139569 1.8764
+140075 1.65346
+140700 1.64945
+141232 1.65112
+141900 1.91037
+142419 2.22762
+143076 2.55301
+143786 3.24549
+144434 4.46618
+145078 5.56588
+145806 6.78385
+146356 7.52602
+147000 8.16321
+147625 8.47157
+148213 8.02486
+148848 6.28328
+149584 5.68576
+150092 5.39
+150796 4.80182
+151284 4.23075
+151929 4.11894
+152621 4.20791
+153241 4.25038
+153910 4.5694
+154589 5.1153
+155259 5.57486
+156019 5.01675
+156669 3.2529
+157624 2.86433
+158139 2.48661
+158640 2.81211
+159281 3.09582
+159843 2.8347
+160485 2.99018
+161077 3.11133
+161679 3.43317
+162205 3.73716
+162840 3.86467
+163380 4.11395
+163927 4.61316
+164644 5.40716
+165214 6.1557
+165838 6.92117
+166416 7.57168
+166973 7.95296
+167561 8.38052
+168195 9.0707
+168935 7.26524
+169455 5.18569
+170089 4.80735
+170811 4.76684
+171416 4.95901
+171970 5.46024
+172509 6.20624
+173151 7.12803
+173695 7.82849
+174330 8.05557
+174996 8.63583
+175752 7.40686
+176406 5.04964
+177147 2.40084
+177745 2.36927
+178430 2.39017
+179046 2.54348
+179783 2.80928
+180404 3.29495
+180932 3.82029
+181626 3.56846
+182202 3.45644
+182845 2.55697
+183385 1.57063
+184021 1.11445
+184525 0.838232
+185172 1.00765
+185691 1.33977
+186203 1.76375
+186864 2.51935
+187466 3.30773
+188221 4.26613
+188943 5.01143
+189513 4.98645
+190218 3.40893
+190745 1.96939
+191462 1.22438
+191968 2.07067
+192557 3.43719
+193163 4.25001
+193826 4.76829
+194397 5.33551
+195125 6.23595
+195755 6.19693
+196544 5.16894
+197138 4.72173
+197716 3.97851
+198335 3.66636
+198937 3.23697
+199576 2.73765
+200222 2.86121
+200936 3.4923
+201557 3.43895
+202293 3.51667
+203155 3.47047
+203831 3.63806
+204488 3.6494
+204939 3.8633
+205376 4.0596
+205996 4.38598
+206396 4.30333
+206799 3.11779
+207526 2.87562
+207928 2.92446
+208493 2.58157
+209176 2.90773
+209888 3.26039
+210587 3.79433
+211269 4.50322
+212134 5.62737
+212911 5.20975
+213729 3.45862
+220694 4.45684
+221320 4.77237
+223839 5.74008
+224401 6.29542
+224961 6.07547
+225538 5.31366
+226237 4.96982
+226995 4.44926
+227578 4.47942
+228206 4.27658
+228841 4.24558
+229518 3.9603
+230222 3.3301
+230860 3.18082
+231503 3.00881
+232037 2.94172
+232639 2.72193
+233181 2.40784
+233830 2.52021
+234353 2.63409
+234998 2.90572
+235630 3.12099
+236170 3.0703
+236748 3.24624
+237336 3.73221
+237954 4.0751
+238511 4.87229
+239134 5.0686
+239735 6.46924
+240393 7.53352
+241067 7.95995
+241706 5.41677
+242326 4.14772
+242952 3.86834
+243604 3.33989
+244305 2.95432
+244863 2.97347
+245553 3.18795
+246465 1.96881
+246867 1.16531
+247404 0.883094
+248028 1.02926
+248585 1.17532
+249211 1.47432
+249765 1.73956
+250500 2.27662
+251064 1.89775
+251758 1.60952
+252287 1.55914
+252925 1.43391
+253623 1.28773
+254325 1.51692
+254858 1.77315
+260516 0.558187
+261083 0.424324
+261770 0.516141
+262442 0.845169
+263321 1.33613
+263836 1.41006
+267998 2.68056
+268617 2.85422
+269249 2.96486
+269968 3.26001
+270708 3.65724
+271368 4.27093
+271985 4.83828
+272624 5.4834
+273253 5.94375
+273850 5.58841
+274370 5.60532
+274946 4.68481
+275565 3.39294
+276106 1.42433
+276745 0.14019
+277330 0.983548
+277933 1.19207
+278644 1.00408
+279222 1.33033
+279883 1.81254
+280522 2.18602
+281202 2.64059
+281905 2.58035
+282523 1.81293
+283198 1.31811
+283819 1.88899
+284588 2.29474
+285137 1.93007
+285779 1.40169
+286419 1.44213
+287099 1.44509
+287695 1.50468
+288356 1.65228
+288895 1.84565
+289598 2.0245
+290216 2.13871
+290944 1.4197
+291513 1.38283
+292225 1.83001
+292816 2.22607
+293574 1.91082
+294118 1.83166
+294754 1.80061
+295452 1.73899
+296096 2.35945
+296793 3.01205
+297474 3.84761
+298114 4.58921
+298900 5.50551
+299610 5.35153
+300295 3.52525
+300910 1.85408
+301567 1.90419
+302230 2.47422
+302969 3.30325
+303527 3.75115
+303948 4.02524
+304590 4.49468
+304991 4.77827
+305585 4.21427
+306234 3.58257
+306649 3.13471
+307231 2.74803
+307884 2.27312
+308511 2.38563
+309264 1.8537
+309863 1.84199
+310465 1.90015
+311227 1.96474
+312017 2.02791
+========================================================== 
+Average of all statistical data: 
+Median: 3.18082
+Average: 3.37233
+Standard Deviation: 1.81028
+75 Quantil: 4.44926

tex/gfx/estimationPath2/mvgPath.csv

@@ -0,0 +1,386 @@
+60.623 21.123 2.1
+60.1654 20.3688 2.3
+59.7266 20.0372 2.4
+60.5129 19.9456 2.2
+61.2438 19.9443 2
+60.1843 20.115 2.4
+59.3821 19.9504 2.6
+59.3631 19.916 2.7
+59.3893 19.9968 2.6
+58.957 19.9826 2.7
+58.5065 19.7842 2.9
+58.2038 19.4828 3.1
+58.0503 19.1977 3.2
+57.6416 18.8281 3.5
+57.3375 18.4343 3.8
+57.2572 18.2356 3.9
+57.2417 18.0313 4
+57.2106 17.738 4.1
+57.3643 17.5175 4.2
+57.4607 17.3399 4.3
+57.6506 17.3193 4.4
+57.8246 17.2262 4.5
+57.9068 16.9798 4.6
+58.0775 16.7712 4.8
+58.4079 16.317 5.1
+58.7154 16.1009 5.3
+59.058 15.9456 5.5
+59.2262 15.9556 5.5
+59.6487 15.8547 5.7
+59.9233 16.0262 5.7
+60.5988 16.3499 5.9
+61.221 16.9285 5.9
+61.6231 17.4966 5.9
+62.0041 18.031 5.9
+62.3521 18.5518 5.9
+62.6246 18.7643 5.9
+62.8059 19.1292 5.9
+62.8237 19.5337 5.9
+62.8211 20.0384 5.9
+62.7856 20.7855 5.9
+62.7038 21.3275 5.9
+62.6254 21.9419 5.9
+62.5881 22.6044 5.9
+62.7084 24.4172 5.9
+62.7806 25.0533 5.9
+62.9458 25.6792 5.9
+62.9321 26.5378 5.9
+62.9763 26.9298 5.9
+62.963 27.4329 5.9
+62.9488 27.7855 5.9
+63.0884 27.5756 5.9
+63.4196 27.3091 5.9
+63.7562 26.9454 5.9
+64.1026 26.6344 5.9
+64.3966 26.2905 5.9
+64.7536 26.0955 5.9
+64.9385 26.0174 5.9
+64.9295 25.9944 5.9
+64.7963 26.3911 5.9
+65.0582 26.5373 5.9
+65.2647 26.6133 5.9
+64.9978 26.9293 5.9
+64.9902 27.0722 5.9
+65.0049 27.119 5.9
+65.2409 27.1044 5.9
+65.4618 27.0557 5.9
+65.6401 27.0801 5.9
+65.0967 27.3894 5.9
+65.0271 27.5673 5.9
+64.9679 27.6189 5.9
+65.0901 27.7263 5.9
+65.299 27.9539 5.9
+65.4649 28.0775 5.9
+66.2054 28.2659 5.9
+67.1889 27.8532 5.9
+67.6481 27.5649 5.9
+68.4694 27.7097 5.9
+68.5968 27.7238 5.9
+68.5858 27.9936 5.9
+68.6293 27.2791 5.9
+68.406 27.0197 5.9
+68.1889 26.578 5.9
+68.1042 25.2694 5.9
+68.0942 24.5163 5.9
+68.1256 23.7997 5.9
+68.1992 23.1404 5.9
+68.2596 22.8631 5.9
+68.0553 22.5537 5.9
+67.9036 21.8923 5.9
+67.6095 21.4085 5.9
+67.2478 19.8145 5.9
+67.0005 18.9957 5.9
+66.8553 17.6831 5.9
+67.0727 16.582 5.9
+66.9132 15.9823 5.9
+67.1672 15.045 5.9
+67.572 14.8388 5.9
+67.8422 14.4907 5.9
+68.2307 14.682 5.9
+68.2025 14.837 5.9
+67.5809 14.7924 5.9
+67.1081 14.9178 5.9
+67.0927 15.1141 5.9
+67.149 15.3724 5.9
+67.2235 15.627 5.9
+67.3749 15.8283 5.9
+67.2881 16.1818 5.9
+67.3289 16.5441 5.9
+66.9019 16.6821 5.9
+66.607 16.9178 5.9
+66.5545 16.9793 5.9
+66.4928 17.0099 5.9
+66.7689 16.8403 5.9
+67.0612 16.9986 5.9
+67.31 16.1543 5.9
+67.3639 14.9526 5.9
+66.9558 14.213 5.9
+66.9837 12.9127 5.9
+67.1531 12.0323 5.9
+67.2216 11.2893 5.9
+67.2732 10.9188 5.9
+67.3787 10.667 5.9
+67.4016 9.77571 5.9
+67.3385 9.00549 5.9
+67.1281 7.9718 5.9
+66.9531 7.2223 5.9
+66.6456 6.79488 5.9
+66.8474 7.3007 5.9
+67.1276 6.88983 5.9
+67.3042 6.44539 5.9
+67.0521 5.75861 5.9
+66.8688 5.52867 5.9
+66.6299 4.99803 5.9
+66.786 4.50627 5.9
+67.1103 5.21175 5.9
+67.2858 5.97657 5.9
+67.4014 7.55376 5.9
+67.4008 8.87914 5.9
+67.4398 10.3076 5.9
+67.3846 10.7295 5.9
+67.3742 10.9593 5.9
+67.281 11.1783 5.9
+67.5126 11.0847 5.9
+67.5873 10.9352 5.9
+67.8278 10.8215 5.9
+67.9027 10.8329 5.9
+67.814 10.6912 5.9
+67.6941 10.6646 5.9
+67.5462 10.6597 5.9
+67.4657 10.8401 5.9
+67.4002 11.2918 5.9
+67.3822 11.6512 5.9
+67.2068 12.4411 5.9
+67.4351 14.6072 5.9
+67.406 15.6802 5.9
+67.3648 16.3241 5.9
+67.2923 17.4361 5.9
+67.0551 18.3157 5.9
+66.6848 18.7564 5.9
+66.5315 19.0185 5.9
+66.5446 19.3506 5.9
+66.6519 19.5379 5.9
+66.8881 19.6391 5.9
+67.0889 19.9271 5.9
+66.8474 21.3239 5.9
+66.2988 23.9165 5.9
+65.789 25.1676 5.9
+65.4662 26.0318 5.9
+65.6744 26.4229 5.9
+65.6983 26.8548 5.9
+65.1977 27.435 5.9
+64.8008 27.706 5.9
+64.3496 27.9979 5.9
+64.142 28.2378 5.9
+63.9894 28.4444 5.9
+63.9905 29.0208 5.9
+63.9889 29.3602 5.9
+64.0097 29.4473 5.9
+64.1884 29.4716 5.9
+64.3578 29.3757 5.9
+64.3295 29.2438 5.9
+64.3443 29.2027 5.9
+64.0606 29.3216 5.9
+63.7954 29.4426 5.9
+63.7142 29.3994 5.9
+63.2018 31.4239 5.9
+62.5424 33.6594 5.9
+62.4109 34.4725 5.9
+62.3347 35.2121 5.9
+62.3317 35.807 5.9
+62.4496 36.1 5.9
+62.7258 36.2135 5.9
+63.0296 36.2441 5.9
+63.1794 36.2153 5.9
+62.7567 36.2405 5.9
+62.6176 36.0756 5.9
+60.7278 36.7864 5.9
+57.9903 37.9256 5.9
+54.8359 38.4263 5.9
+54.2353 38.5079 5.9
+53.4289 38.632 5.9
+52.6491 38.7448 5.9
+51.728 39.1875 5.9
+50.9874 39.5586 5.9
+50.4874 39.8275 5.9
+50.2239 41.0923 5.9
+50.0536 42.0401 5.9
+50.1954 43.653 5.9
+50.1072 44.5382 5.9
+49.6166 44.9821 5.9
+49.4854 45.2822 5.9
+49.2737 45.4285 5.9
+49.1629 45.5658 5.9
+49.0514 45.6249 5.9
+49.0846 45.6636 5.9
+49.2074 45.7177 5.9
+49.3093 45.6999 5.9
+49.2407 45.7462 5.9
+48.5716 45.8134 5.9
+46.3963 45.9575 5.9
+44.9085 45.83 5.9
+43.2005 45.6608 5.9
+42.357 45.7536 5.9
+41.4005 46.0398 5.9
+40.8987 45.8721 5.9
+40.4937 45.3397 5.9
+40.0764 44.9769 5.9
+39.7886 44.8631 5.9
+40.0306 44.0906 5.9
+40.0961 43.1966 5.9
+40.0059 42.9281 5.9
+40.3683 42.366 5.9
+40.5434 42.0224 5.9
+40.5927 41.3632 5.9
+40.5287 40.3026 5.9
+40.5151 39.3681 5.9
+40.4054 39.2057 5.9
+40.298 39.243 5.9
+40.2859 39.3263 5.9
+39.9061 39.6929 5.9
+39.6913 40.0672 5.9
+39.1585 40.7551 5.9
+38.9952 41.1328 5.9
+38.8208 41.5103 5.9
+38.4417 41.0904 5.8
+38.2319 41.1578 5.7
+37.4114 41.8481 5.2
+37.2006 42.2884 4.9
+37.1527 42.4496 4.8
+37.1201 42.781 4.6
+37.0803 42.8106 4.6
+37.0966 42.8885 4.5
+37.1193 42.8951 4.5
+37.0462 42.9111 4.7
+37.0131 42.5782 4.9
+36.9313 42.9025 4.9
+37.5072 45.6002 4.9
+37.6797 46.708 5
+37.7427 46.808 5.1
+38.079 47.1109 5.2
+38.3892 47.2667 5.3
+38.012 47.4141 5.2
+37.3154 47.311 4.9
+37.117 47.0286 4.7
+36.4848 46.8558 4.5
+36.0575 47.031 4.3
+35.7449 46.8081 4
+35.4953 46.6328 4
+35.1314 46.216 4
+35.3539 45.1896 4
+35.415 44.0067 4.2
+34.8904 43.207 4.2
+34.2898 42.9024 4.1
+33.3569 42.7359 4
+32.3009 42.925 3.9
+31.5082 43.1441 3.9
+30.9195 43.2382 3.9
+30.3554 43.3105 3.9
+29.7293 43.4211 3.9
+28.9959 43.3844 3.9
+28.4752 43.3132 3.9
+28.207 43.4027 3.9
+27.7743 43.415 3.9
+27.8013 43.7085 3.9
+27.1386 43.9005 3.9
+27.5258 44.7471 3.9
+27.6947 45.4828 3.9
+28.0287 45.8345 3.9
+25.393 45.5538 3.9
+24.029 45.4814 3.9
+23.5829 45.6302 3.9
+22.6453 45.6271 3.9
+21.5464 45.7839 3.9
+20.9834 45.6325 3.9
+20.4691 45.6516 3.9
+18.2346 45.7591 3.9
+16.7915 45.7409 3.9
+15.5826 45.8829 3.9
+14.9329 45.9395 3.9
+14.3146 45.9717 3.9
+13.8882 45.908 3.9
+13.5508 45.8777 3.9
+13.0146 45.6263 3.9
+12.6799 45.4501 3.9
+12.6718 45.1173 3.9
+12.4714 44.5754 3.9
+12.2556 44.0391 3.9
+12.0216 43.5166 3.9
+12.1952 43.0648 3.9
+12.3662 42.6663 3.9
+12.2853 42.9501 3.9
+12.1474 43.217 3.9
+12.0447 43.3726 3.9
+11.9041 43.6247 3.9
+11.8061 43.8167 3.9
+11.8615 43.7308 3.9
+12.2055 43.6962 3.9
+12.4865 43.775 3.9
+12.7059 43.746 3.9
+12.9525 43.8838 3.9
+13.2143 44.0318 3.9
+13.3311 44.1158 3.9
+13.4112 44.1463 3.9
+13.4948 44.2113 3.9
+13.386 44.1019 3.9
+13.0477 43.2212 3.9
+13.0086 42.7599 3.9
+13.0501 41.2777 3.9
+12.3902 39.4837 3.9
+11.794 37.0612 3.9
+11.3231 35.1037 3.9
+11.1496 33.5679 3.9
+10.9514 32.8202 3.9
+10.5827 32.3798 3.9
+10.0803 32.0129 3.9
+9.76476 31.8586 3.9
+9.38231 31.8813 3.9
+8.9438 31.8746 3.9
+8.12399 31.9185 3.9
+7.85315 32.0956 3.9
+7.55062 32.4131 3.9
+7.34641 32.9413 3.9
+7.28741 32.877 3.9
+7.39901 32.5363 3.9
+7.9067 31.839 3.9
+9.00418 31.4286 3.9
+9.7845 31.1702 3.9
+10.4002 31.0846 3.9
+10.7104 31.2884 3.9
+10.9269 31.4112 3.9
+11.2339 31.3783 3.9
+11.2287 31.2915 3.9
+11.2155 31.1154 3.9
+11.1674 31.0809 3.9
+11.1323 31.126 3.9
+11.0599 31.1577 3.9
+10.8674 31.2928 3.9
+10.4687 31.4763 3.9
+10.1101 31.5179 3.9
+9.84586 31.716 3.9
+9.90833 31.7398 3.9
+9.81917 31.8688 3.9
+9.67723 31.8035 3.9
+9.56416 31.7816 3.9
+9.81074 31.6154 3.9
+10.8679 32.0294 3.9
+10.9698 34.0541 3.9
+10.6292 36.2087 3.9
+10.2928 36.88 3.9
+10.2991 37.0838 3.9
+10.4218 37.0748 3.9
+10.1 36.937 3.9
+9.66561 36.7488 3.9
+9.23498 36.6121 3.9
+9.12556 36.6262 3.9
+8.39619 36.7655 3.6
+7.98224 37.1558 3.4
+7.68315 37.5008 3.2
+7.23858 37.7276 3
+6.28239 37.4556 2.8
+6.16993 37.6871 2.7
+5.07466 37.2835 2.5
+4.24955 36.6768 2.5
+4.02493 36.548 2.5
+3.83764 36.4497 2.5
+3.82022 36.3841 2.5

tex/gfx/radiusFiles/Path0_Impoverishment.csv

@@ -0,0 +1,346 @@
+2.82371
+1.15688
+2.66101
+3.62845
+1.65395
+1.10148
+0.824665
+1.80226
+0.400003
+0.729269
+0.419109
+0.826914
+0.322061
+0.482782
+0.926036
+0.375456
+1.16181
+0.870511
+0.35774
+0.65151
+0.676646
+1.74394
+0.506561
+1.78666
+0.81899
+0.302236
+0.274294
+0.565119
+0.341947
+0.499171
+0.475495
+0.129367
+0.595786
+0.238822
+0.22408
+0.357689
+0.108416
+0.423452
+0.873407
+0.433726
+1.34655
+0.433855
+1.03342
+0.566717
+0.369552
+0.343476
+0.529269
+0.782133
+0.6785
+0.235192
+0.784771
+0.455166
+9.9765
+0.946013
+1.0754
+0.499518
+0.614235
+0.456418
+0.362809
+0.619638
+0.911013
+0.804793
+0.353476
+0.347452
+0.548574
+0.73867
+0.659939
+1.15072
+0.432056
+10.4731
+9.88496
+8.66971
+9.38957
+8.63318
+0.808576
+0.57405
+1.02543
+9.45916
+10.4146
+11.7184
+13.4513
+11.6114
+9.82192
+10.5893
+1.59072
+1.46052
+1.41658
+2.74026
+0.948384
+2.70132
+2.39944
+2.10801
+1.72052
+1.22646
+2.09197
+1.08164
+0.987668
+1.62745
+4.30922
+0.348066
+0.535686
+3.63851
+0.844246
+1.29248
+2.905
+0.714802
+1.46413
+1.08413
+0.6074
+0.539971
+3.55177
+1.20214
+0.178696
+0.559726
+2.23941
+0.721052
+1.22955
+0.431312
+0.449234
+0.762644
+1.02472
+3.16637
+2.79047
+4.39959
+1.13543
+1.94509
+1.80582
+4.40001
+5.3542
+5.93019
+5.94941
+1.7438
+1.45105
+0.951385
+2.65667
+2.46069
+1.39006
+2.89081
+3.16371
+5.49198
+4.80496
+2.31915
+1.87068
+11.5674
+9.20287
+5.21919
+4.14241
+3.96802
+5.14315
+1.94785
+3.21569
+3.10741
+2.72719
+3.57697
+2.10498
+2.65353
+2.08635
+19.2479
+16.2262
+13.6266
+12.6671
+11.8583
+11.7191
+11.115
+0.722672
+10.1735
+9.39574
+0.378835
+8.95146
+9.45152
+1.02045
+0.821988
+0.793229
+0.71375
+1.42906
+0.314609
+0.354821
+0.442273
+5.74042
+5.26903
+6.25593
+5.69902
+7.06927
+6.82334
+7.59253
+2.29832
+2.51974
+3.95953
+1.44722
+3.05548
+1.26331
+1.33507
+1.36412
+3.67633
+3.00612
+1.49565
+1.94929
+3.68127
+3.5021
+3.9223
+4.97409
+3.67087
+0.795886
+0.721253
+1.02432
+1.07864
+1.67231
+2.18877
+1.61779
+3.98709
+3.08554
+3.00285
+2.91898
+1.98896
+2.60403
+5.35355
+2.78152
+4.33055
+4.45385
+4.90993
+3.84414
+4.69191
+4.34297
+4.80911
+4.89517
+3.14609
+3.38278
+4.65188
+1.58585
+1.9419
+1.27359
+1.76142
+1.26847
+0.738181
+0.826962
+1.05069
+1.65183
+3.16512
+3.15061
+3.70038
+1.64194
+1.74689
+0.78019
+0.789883
+0.326002
+1.19169
+0.676993
+1.80053
+0.96639
+1.09706
+1.52984
+2.02973
+0.745047
+2.78833
+3.28953
+0.965744
+0.989919
+1.00623
+1.31936
+1.16704
+1.4461
+1.11283
+1.25798
+1.47591
+1.19954
+0.95618
+1.5036
+1.86226
+1.82215
+1.75738
+1.27515
+2.31258
+0.60795
+0.377009
+0.381589
+0.165465
+1.05728
+1.28323
+1.0347
+1.85635
+1.05554
+4.5995
+5.62714
+3.76525
+4.88076
+4.6149
+3.31377
+3.16611
+2.09948
+1.54193
+1.77975
+1.84006
+1.91638
+1.21429
+0.393537
+0.995583
+1.06526
+1.88906
+2.47388
+2.64276
+3.82558
+3.21295
+3.52242
+0.843546
+0.601535
+0.391719
+1.27751
+0.706189
+0.634887
+1.36661
+0.987771
+2.39567
+0.352925
+0.488926
+2.70833
+1.20587
+0.616957
+2.1711
+6.87905
+6.05344
+8.39922
+8.25076
+8.03084
+8.4918
+8.96353
+9.02634
+1.40693
+2.37415
+3.40815
+2.79137
+2.5205
+1.15865
+1.47339
+1.74809
+2.63664
+0.309279
+1.46779
+2.019
+0.474389
+2.61696
+2.60538
+2.52929
+1.13013
+6.64187
+7.67174
+5.53069

tex/gfx/radiusFiles/Path1_Multimodal.csv

@@ -0,0 +1,369 @@
+1.82601e-07
+19.0152 //ignoring, since this is at the start and we have a uniformal apriori
+1.08697
+0.826885
+1.52767
+5.51301
+6.16372
+7.83987
+2.3847
+3.64233
+4.18353
+2.22118
+3.51655
+3.47266
+4.91746
+4.39668
+11.6044
+4.59689
+1.09196
+2.13869
+4.68188
+3.69582
+3.92093
+2.96581
+3.33971
+3.79452
+5.08094
+4.22572
+3.42407
+2.32395
+1.84053
+3.18077
+0.994648
+1.5823
+0.69208
+4.05446
+1.72875
+3.40068
+4.74194
+3.92009
+3.74152
+2.3799
+1.04048
+0.394101
+2.58785
+3.27946
+3.66226
+0.791286
+3.13148
+3.50486
+2.33711
+1.07515
+0.401021
+0.940327
+2.40313
+6.07187
+4.07238
+5.43062
+6.22169
+0.629007
+7.4813
+6.90284
+7.92044
+5.98698
+5.99492
+4.15208
+3.49511
+3.74395
+1.76749
+3.70597
+2.16305
+3.16889
+2.88837
+0.781144
+1.81259
+1.66742
+4.11273
+4.48033
+4.78505
+4.76734
+0.0889085
+0.454082
+0.19378
+0.304057
+0.209861
+0.341934
+0.100512
+0.461653
+0.561476
+0.200157
+2.1194
+0.562012
+2.08194
+1.42821
+1.82238
+2.25292
+1.27063
+0.914829
+3.22714
+3.88725
+1.90544
+4.13254
+1.63303
+0.846373
+1.57194
+3.53125
+0.813703
+2.52402
+1.04521
+2.97698
+3.59358
+3.82164
+2.88698
+2.39697
+2.16464
+2.20219
+1.42386
+0.226892
+1.03765
+2.62223
+4.62995
+0.904111
+0.834088
+1.14218
+1.40159
+0.822567
+0.933673
+0.0604108
+1.58268
+1.97644
+1.28097
+1.95268
+2.75768
+3.22913
+2.41074
+2.4304
+2.37131
+0.31879
+1.41585
+0.832249
+2.92022
+2.745
+1.67361
+1.07993
+1.69897
+2.29614
+2.6867
+1.94474
+2.44305
+3.69805
+2.24566
+2.48212
+2.05655
+1.1048
+2.74036
+1.92892
+1.51408
+1.09445
+0.982885
+0.617759
+2.89783
+2.20071
+2.37763
+0.140607
+1.93755
+2.71863
+1.7265
+2.62364
+2.469
+2.53277
+2.02097
+5.92603
+1.03452
+0.72445
+3.26978
+2.16294
+3.76293
+3.55316
+3.26994
+2.78871
+3.07049
+2.62551
+2.9203
+1.22425
+2.00283
+1.64691
+1.19245
+1.00549
+0.777423
+0.536492
+0.156838
+0.984232
+0.791655
+0.250046
+0.985569
+0.572557
+1.83123
+0.922981
+0.337596
+0.622945
+1.3404
+3.10989
+2.49197
+2.10554
+0.290929
+2.29228
+2.47081
+1.38589
+2.38961
+2.38432
+1.09607
+0.749452
+0.614382
+4.16285
+4.95206
+0.639451
+1.68922
+0.644013
+2.22044
+1.47207
+0.414494
+0.578721
+1.9984
+0.639066
+7.11493
+5.67659
+5.49748
+5.37884
+1.55729
+0.850091
+1.13764
+1.32835
+2.69196
+5.70526
+5.83195
+5.5606
+6.49758
+5.74738
+5.5201
+5.48617
+4.16315
+2.84061
+0.916203
+1.48394
+3.08875
+1.54412
+0.75578
+0.607576
+0.287051
+0.730486
+0.530102
+0.750293
+1.48812
+1.20501
+0.809046
+0.743785
+3.29255
+2.46543
+2.27236
+2.38194
+2.17307
+1.60469
+0.545387
+0.781305
+0.520123
+0.349319
+1.27223
+0.0185229
+2.01793
+1.39625
+0.58897
+0.764092
+0.598471
+2.1681
+1.9295
+1.51571
+1.74196
+2.43599
+1.21431
+2.98078
+1.23229
+1.57808
+1.90309
+1.365
+0.779948
+2.6856
+1.42747
+0.270431
+2.13889
+1.62769
+0.719854
+1.39268
+1.54215
+0.829313
+0.0281057
+1.63504
+1.3314
+1.91091
+0.841914
+1.15337
+1.09602
+0.766968
+0.977623
+2.19634
+6.74175
+1.62684
+1.06827
+3.03705
+2.50637
+1.15875
+2.62203
+5.26134
+3.88014
+3.22852
+1.5502
+1.19221
+1.06078
+1.77681
+0.551977
+0.164431
+0.0648866
+1.81009
+3.17041
+0.0393285
+0.837597
+2.02422
+0.0513751
+2.14283
+0.138393
+8.40005
+8.3662
+5.96594
+4.31489
+5.50724
+2.83485
+4.21201
+1.37662
+0.329763
+0.494459
+1.7515
+8.03592
+5.92561
+5.02064
+4.27237
+3.41208
+3.38115
+2.99832
+3.31955
+2.75733
+2.12782
+1.91157
+0.290451
+0.255636
+1.51557
+1.47829
+2.12031
+2.09166
+1.24055
+1.7923
+1.04011
+1.33244
+1.01705
+0.879654
+1.13949
+1.23183
+3.17408
+1.61283
+0.409391
+1.2868